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      Approaches to Studying Policy Representation : Studying Policy Representation

      Legislative Studies Quarterly
      Wiley-Blackwell

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          Partisans without Constraint: Political Polarization and Trends in American Public Opinion

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            The Strength of Issues: Using Multiple Measures to Gauge Preference Stability, Ideological Constraint, and Issue Voting

            A venerable supposition of American survey research is that the vast majority of voters have incoherent and unstable preferences about political issues, which in turn have little impact on vote choice. We demonstrate that these findings are manifestations of measurement error associated with individual survey items. First, we show that averaging a large number of survey items on the same broadly defined issue area—for example, government involvement in the economy, or moral issues—eliminates a large amount of measurement error and reveals issue preferences that are well structured and stable. This stability increases steadily as the number of survey items increases and can approach that of party identification. Second, we show that once measurement error has been reduced through the use of multiple measures, issue preferences have much greater explanatory power in models of presidential vote choice, again approaching that of party identification.
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              Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953–1999

              At the heart of attitudinal and strategic explanations of judicial behavior is the assumption that justices have policy preferences. In this paper we employ Markov chain Monte Carlo methods to fit a Bayesian measurement model of ideal points for all justices serving on the U.S. Supreme Court from 1953 through 1999. We are particularly interested in determining to what extent ideal points of justices change throughout their tenure on the Court. This is important because judicial politics scholars oftentimes invoke preference measures that are time invariant. To investigate preference change, we posit a dynamic item response model that allows ideal points to change systematically over time. Additionally, we introduce Bayesian methods for fitting multivariate dynamic linear models to political scientists. Our results suggest that many justices do not have temporally constant ideal points. Moreover, our ideal point estimates outperform existing measures and explain judicial behavior quite well across civil rights, civil liberties, economics, and federalism cases.
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                Author and article information

                Journal
                Legislative Studies Quarterly
                Legislative Studies Quarterly
                Wiley-Blackwell
                03629805
                February 2016
                February 12 2016
                : 41
                : 1
                : 181-215
                Article
                10.1111/lsq.12110
                aa27a9c2-8568-4cd0-af41-11dc37f4f72b
                © 2016

                http://doi.wiley.com/10.1002/tdm_license_1.1

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